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CATEGORIES:Isaac Newton Institute Seminar Series
SUMMARY:Performing computation with DNA - Neil Dalchau (Mi
crosoft (UK))
DTSTART;TZID=Europe/London:20160121T141500
DTEND;TZID=Europe/London:20160121T150000
UID:TALK64667AThttp://talks.cam.ac.uk
URL:http://talks.cam.ac.uk/talk/index/64667
DESCRIPTION:The development of technology to read and write DN
A quickly and cheaply is enabling new opportunitie
s for programming biological systems. One example
of this is DNA computing\, a field devoted to impl
ementing computation in purely biological material
s. The hope is that this would enable computation
to be performed inside cells\, which could pave th
e way for so-called &ldquo\;smart therapeutics&rdq
uo\;. Naturally\, what we have learned in computer
science can be applied to DNA computing systems\,
and has enabled the implementation of a wide vari
ety of examples of performing computation. Example
s include DNA circuits for computing a square root
\, implementing artificial neural networks\, and a
general scheme for describing arbitrary chemical
reaction networks (CRNs)\, which itself can be tho
ught of as a compiler.
We have used such a
CRN compiler of DNA circuitry to implement the ap
proximate majority (AM) algorithm\, which seeks to
determine the initial majority of a population of
agents holding different beliefs. In its simplest
form\, the algorithm can be described by three ch
emical reactions. In this talk\, I will describe h
ow we implemented\, characterized and modelled a p
urely DNA implementation of the AM reactions. Alon
g the way\, I will demonstrate our software platfo
rm for programming biological computation. The pla
tform brings together a variety of stochastic meth
ods that are relevant for both programming and und
erstanding biochemical systems\, including stochas
tic simulation\, integration of the chemical maste
r equation\, a linear noise approximation\, and Ma
rkov chain Monte Carlo methods for parameter infer
ence. I will also show preliminary work on synthe
sizing CRNs with specified probabilistic behaviour
s.
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